dqs.torch.loss.RankedProbabilityScore

This class is used to compute ranked probability score.

class RankedProbabilityScore(
    distribution,
    loss_boundaries)

Parameters:

Args	Type	Description
distribution	dqs.distribution	Object from dqs.distribution package to store probability distribution.
boundaries	list (float)	Boundaries used in ranked probability score.

loss(pred, y, e=None)

Parameters:

Args	Type	Description
pred	Tensor (float)	Estimated probability distribution to be evaluated.
y	Tensor (float)	One-dimensional tensor to represent labels from a dataset.
e	Tensor (bool)	One-dimensional tensor to represent censored (False) or uncensored (True).

Return type: Tensor representing a single float.

Example

The following code computes the ranked probability score based on estimated probability distributions (pred) and labels (y).

boundaries = torch.linspace(0.0, 10.0, 11)
dist = dqs.distribution.DistributionLinear(boundaries)
loss_fn = dqs.loss.RankedProbabilityScore(dist, boundaries)
pred = torch.Tensor([[0.4,0.6],[0.2,0.8]])
y = torch.Tensor([5.0,5.0])
loss = loss_fn.loss(pred, y)